Market-based approach for cooperation and coordination among multiple autonomous vehicles

Multi-robot systems (MRS) have recently become a topic of interest in the field of robotics research since they can be utilized in many diverse areas of applications. The fact that MRS applications are complex, therefore, they must be divided into a set of sub-tasks that necessitates the incorporation of a task allocation, which will be responsible for assigning the robots to the available tasks to be executed. This research interest of multiple agents is extended to the intelligent transportation systems society, through considering the transportation vehicles as the mobile robots. Currently, the number of the intelligent vehicles on the road is increasing, which requires more coordination and cooperation among them. In this paper, a market-based approach is proposed for solving the task allocation problem in multiple autonomous vehicles system. The proposed approach addresses general task allocation problem, it generates a solution that maximizes the overall performance and minimizes the total cost of the system objective cost function. This is taking into consideration the real world constraints of the system, the requirements of the tasks, and the capabilities of the vehicles. Different scenarios are tested in simulation and real-world experiments. The obtained results show the high performance of the proposed approach in an efficient manner, moreover the applicability in real-world situations.